Chief Cloud AI Infrastructure Architect

2 weeks ago


Lucknow, Uttar Pradesh, India Binoloop Full time

We are seeking a seasoned Chief Cloud AI Infrastructure Architect to lead our cloud-based AI operations initiatives at Binoloop.

This is a unique opportunity to shape the future of AI-driven products and services by architecting, implementing, and maintaining state-of-the-art AI SaaS on Google Cloud Platform (GCP).

You will work across multiple domains, including CICD, Security, IaC, ETL pipelines, monitoring, and container orchestration, to ensure our infrastructure and machine learning pipelines run seamlessly, securely, and efficiently.

The ideal candidate will have strong experience with GCP, CI/CD tools, security frameworks, IaC, ETL & data ops, monitoring & observability, containerization & orchestration, and performance optimization. Excellent communication and problem-solving skills are essential for success in this role.

Beyond technical expertise, we're looking for leaders who can foster collaboration, drive innovation, and navigate the ever-evolving landscape of AI and DevOps.

About the Role:

  • AIOps & Cloud Architecture: Design, deploy, and optimize AIOps solutions on GCP to streamline ML workflows, reduce latency, and ensure high availability.
  • CICD & DevOps: Develop and maintain advanced CI/CD pipelines integrating best practices for testing, deployment, and version control, leveraging tools like GitLab CI, Jenkins, or GitHub Actions.
  • Security & SecOps: Implement end-to-end security frameworks, including vulnerability scanning, secrets management, intrusion detection, and SIEM integration, ensuring compliance with industry standards and data protection regulations.
  • IaC & Terraform: Utilize Terraform to automate infrastructure provisioning, configuration management, and deployments, standardizing and templatizing infrastructure code for scalability and repeatability.
  • ETL & Data Operations: Collaborate with data engineering teams to build and enhance ETL pipelines, optimizing data flows for accuracy, accessibility, and reliability in machine learning initiatives.
  • Monitoring & Observability: Set up comprehensive monitoring solutions using tools like Prometheus, Grafana, and Stackdriver, analyzing metrics, logs, and traces to identify bottlenecks and performance issues.
  • Kubernetes & Containerization: Orchestrate multi-staged container builds and manage complex Kubernetes deployments, focusing on scalability, fault tolerance, and cost efficiency.
  • Latency Optimization & GPU Deployment: Implement strategies for reducing end-to-end latency in ML workflows, leveraging GPU-accelerated instances for high-performance workloads and optimal resource utilization.

Benefits:

  • Competitive Salary: ₹18,00,000 to ₹26,00,000 per annum (with stock options).
  • Culture of Learning: Access continuous learning opportunities, R&D projects, and professional development resources.
  • Supportive Environment: Join a team that values collaboration, innovation, and hyperscale growth.

Requirements:

  • 6+ years of experience in AIOps, DevOps, SRE, or a similar role.
  • Demonstrated expertise in GCP, CI/CD tools, security frameworks, IaC, ETL & data ops, monitoring & observability, containerization & orchestration, and performance optimization.


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